Transportation line combination method, electronic device, storage medium, and computer program product

Abstract

The present application provides a transportation line combination method, an electronic device, a storage medium, and a computer program product. The method comprises: acquiring a plurality of transportation lines in a logistics network; combining the plurality of transportation lines according to a line combination constraint, and obtaining an initial line set, the line combination constraint comprising a first empty driving constraint, and the first empty driving constraint being used for constraining empty driving distances and / or empty driving times between different lines in the same initial line set; and determining a line combination result on the basis of the initial line set, and outputting same. During the combination process of the transportation lines, empty driving conditions are taken into account, so that the initial line set obtained after combination has good performance in the empty driving dimension, and empty driving conditions of a vehicle are alleviated.

Description

Methods for combining transport routes, electronic equipment, storage media, and computer program products Technical Field

[0001] This application relates to the field of logistics and transportation technology, specifically to a method for combining transportation routes, electronic equipment, storage media, and computer program products.

[0002] Background of the Invention

[0003] With the rapid development of global e-commerce, the modern logistics industry faces increasingly complex transportation demands and challenges. To address this, logistics companies are constantly exploring various methods to optimize transportation route combinations in order to improve logistics efficiency and meet customer needs.

[0004] Currently, most transportation route combination plans are completed by experienced professionals. However, due to limitations in the experience and capabilities of these personnel, manually completed combination plans are prone to local optima, resulting in significant empty runs when operating according to these plans. Summary of the Invention

[0005] This application provides a method for combining transportation routes, an electronic device, a storage medium, and a computer program product to solve the problem of serious empty vehicle operation under existing transportation route combination methods.

[0006] A first aspect of this application provides a method for combining transportation routes. The method includes: acquiring multiple transportation routes in a logistics network; combining the multiple transportation routes according to route combination constraints to obtain an initial route set; wherein the route combination constraints include: a first empty-run constraint, the first empty-run constraint being used to constrain the empty-run distance and / or empty-run time between different routes in the same initial route set; determining and outputting a route combination result based on the initial route set. For example, the initial route set is used as the route combination result and output.

[0007] A second aspect of this application provides a method for combining transportation routes. The method includes: acquiring multiple transportation routes in a logistics network; combining the multiple transportation routes according to route combination constraints to obtain an initial route set; wherein the route combination constraints include: a first empty-run constraint, which is used to constrain the empty-run distance and / or empty-run time between different routes in the same initial route set; based on the initial route set, performing multiple rounds of combination on the multiple transportation routes according to a tabu search algorithm to obtain multiple rounds of combination results, wherein each round of combination results includes multiple intermediate route sets; selecting the optimal combination result from each round of combination results as the route combination result and outputting it.

[0008] A third aspect of this application provides a method for combining transportation routes. The method includes: responding to a user's target input, acquiring multiple transportation routes in a logistics network and determining a response time limit; if the response time limit is less than or equal to a duration threshold, combining the multiple transportation routes according to route combination constraints to obtain an initial route set; wherein the route combination constraints include: a first empty-run constraint, which constrains the empty-run distance and / or empty-run time between different routes in the same initial route set; outputting the initial route set as a route combination result; if the response time limit is greater than the duration threshold, combining the multiple transportation routes according to the route combination constraints to obtain an initial route set; based on the initial route set, performing multiple rounds of combination on the multiple transportation routes according to a tabu search algorithm to obtain multiple rounds of combination results, wherein each round of combination results includes multiple intermediate route sets; selecting the optimal combination result from each round of combination results as the route combination result and outputting it.

[0009] A fourth aspect of this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a method for combining transport routes as described in the first, second, or third aspect.

[0010] A fifth aspect of this application provides a storage medium storing a computer program that, when executed by a processor, implements the method for combining transport routes as described in the first, second, or third aspect.

[0011] A sixth aspect of this application provides a computer program product, comprising: a computer program that, when executed by a processor, implements the method for combining transport routes as described in the first, second, or third aspect.

[0012] As can be seen from the above technical solution, the embodiments of this application can realize the automatic combination of transportation routes, thereby avoiding the local optima caused by manual combination of transportation routes. Meanwhile, the route combination constraint includes a first empty-run constraint, which is used to constrain the empty-run distance and / or empty-run time between different routes in the same initial route set. By taking empty-run conditions into account during the combination of transportation routes, the resulting initial route set exhibits good performance in the empty-run dimension, mitigating vehicle empty-running issues.

[0013] Brief description of the attached figures

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0015] Figure 1 is one of the flowcharts of a method for combining transportation routes according to an embodiment of this application;

[0016] Figure 2 is a second flowchart of a method for combining transportation routes provided in an embodiment of this application;

[0017] Figure 3 is a schematic diagram of the method for combining transportation routes in an enterprise system according to an embodiment of this application;

[0018] Figure 4 is a third flowchart of a method for combining transportation routes provided in an embodiment of this application;

[0019] Figure 5 is a schematic diagram of one of the structural components of a transportation route assembly provided in an embodiment of this application;

[0020] Figure 6 is a second structural schematic diagram of a combined device for a transportation line provided in an embodiment of this application;

[0021] Figure 7 is a third structural schematic diagram of a combined device for a transportation line provided in an embodiment of this application;

[0022] Figure 8 is a schematic diagram of the electronic device structure provided in an embodiment of this application.

[0023] Methods of implementing the present invention

[0024] Unless otherwise defined, the technical or scientific terms used in the embodiments of this specification shall have the ordinary meaning understood by one of ordinary skill in the art to which this specification pertains. The terms "first," "second," and similar terms used in the embodiments of this specification do not indicate any order, quantity, or importance, but are merely used to avoid confusion of constituent elements.

[0025] Unless the context otherwise requires, throughout this specification, "a plurality of" means "at least two," and "including" is interpreted as open-ended or encompassing, that is, "including, but not limited to." In the description of this specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this specification. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example.

[0026] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this specification.

[0027] Overview

[0028] As described in the background section, the combination of transportation routes in existing logistics networks is mostly done by experienced professionals. Due to human limitations, it's difficult to consider relevant indicators such as average vehicle mileage, empty mileage, the number of uncombined individual routes, and overall operational information from a holistic perspective. This not only makes it difficult to measure and control overall costs but also easily leads to local optima, resulting in significant empty vehicle runs when operating according to the combined plan.

[0029] To address the aforementioned problems, the inventors of this application have considered the empty-running situation during the combination process to create combinations with good empty-running performance. Therefore, embodiments of this application provide a method for combining transportation routes, aiming to achieve automatic combination of transportation routes and thus avoid local optima caused by manual combination of transportation routes. Simultaneously, the route combination constraints include a first empty-running constraint, which constrains the empty-running distance and / or empty-running time between different routes in the same initial route set. By considering the empty-running situation during the combination of transportation routes, the resulting initial route set exhibits good performance in the empty-running dimension, mitigating vehicle empty-running issues. The specific solution is described in detail below through embodiments.

[0030] Exemplary methods

[0031] This application provides an exemplary description of a method for combining transportation routes, as shown in Figure 1. The method for combining transportation routes includes:

[0032] S101: Obtain multiple transportation routes in the logistics network.

[0033] In this step, the logistics network is a network composed of logistics nodes used to realize logistics transportation. In some embodiments, the logistics network can be a network composed of logistics nodes in a designated business area. Each logistics node can be considered a service point or outlet (logistics outlet). For example, a service point is the origin, transit point, or destination of goods. Goods may pass through one or more service points during transportation within the logistics network. The transportation routes in the logistics network are the transportation routes between the logistics nodes. For example, region A has 10 logistics outlets, and there are cargo transportation relationships between these outlets. These logistics outlets and their transportation relationships constitute the logistics network of region A. The transportation routes of this logistics network are the routes along which goods are transported between the logistics outlets.

[0034] S102: Combine multiple transportation routes according to the route combination constraint to obtain the initial route set.

[0035] It should be noted that the initial set of routes can be considered as a set of routes with good empty-run conditions. Therefore, it is necessary to pre-set route combination constraints with the aim of improving empty-run conditions. When combining transport routes, the generated route combination that satisfies the route combination constraints is the initial set of routes with good empty-run conditions. The content of the route combination constraints may include, for example, a first empty-run constraint, which constrains the empty-run distance and / or empty-run time between different routes within the same initial set. For example, the first empty-run constraint includes: the empty-run distance must not exceed 10 kilometers. Then, when combining transport routes according to the first empty-run constraint, if transport route A and transport route B are combined, and the vehicle's empty-run distance during the transportation of goods along the two routes is 5 kilometers, then transport routes A and B can be successfully combined. If the vehicle's empty-run distance during the transportation of goods along the two routes is 15 kilometers, then transport routes A and B cannot be successfully combined.

[0036] It is understandable that combining multiple transport routes can generate multiple different route combinations, and the number of transport routes in each combination will not be the same. This application does not limit the rules followed during the combination. These rules can be arbitrary; for example, they can be random combination rules. Alternatively, they can be maximum number rules, where the transport routes are combined with a fixed number of routes, so that when multiple initial route sets are generated, all of them contain the same number of transport routes.

[0037] S103: Determine and output the route combination results based on the initial route set.

[0038] In one example, the initial set of lines can be output as the result of line combination.

[0039] It should be noted that this application does not limit the output method of the line combination results. It can be any output method. For example, it can be output in a vivid and engaging way with images and text, or it can be output via voice broadcast. In some embodiments, the line combination results can be directly output to the management department within the enterprise that submitted the line combination request. Here, the aforementioned management department within the enterprise can be understood as an electronic device under that department; that is, the line combination results are output to an electronic device under the corresponding management department. For example, the line combination results can be output to the corporate email of an employee under the corresponding management department.

[0040] In some embodiments, to avoid omitting individual transport routes, each transport route in the target route set is output separately; wherein, the target route set includes transport routes other than the initial route set. It should be noted that not every transport route in the logistics network can be successfully combined with other transport routes. For example, during the process of combining remaining transport routes, due to conflicts in transport time, one or more transport routes cannot be successfully combined with all remaining transport routes. Omitting these uncombinable transport routes would have more serious consequences. Therefore, these uncombinable transport routes can be output separately for subsequent processing.

[0041] In this embodiment, automatic combination of transportation routes can be achieved, thereby avoiding local optima caused by manual combination of transportation routes. Simultaneously, the route combination constraint includes a first empty-run constraint, which constrains the empty-run distance and / or empty-run time between different routes in the same initial route set. By taking empty-run conditions into account during the combination of transportation routes, the resulting initial route set exhibits good performance in the empty-run dimension, mitigating vehicle empty-run issues.

[0042] In some embodiments of this application, the route combination constraint further includes a second empty-run constraint, which is used to constrain the ratio of the total empty-run distance to the total transport mileage between different transport routes in the same initial route set.

[0043] It should be noted that the ratio of total empty-run distance to total transport mileage can be considered an indicator of transport efficiency. A larger ratio indicates lower transport efficiency, while a smaller ratio indicates higher efficiency. Therefore, considering both the first and second empty-run constraints during the combination of transport routes can not only improve empty-run conditions but also enhance transport efficiency. In this embodiment, the total transport mileage can be the total length of all transport routes in the initial route set.

[0044] In some embodiments, the route combination constraint also includes a third empty-run constraint, which constrains the distance from the destination of the last transport route in the initial route set to the origin of the first transport route. For example, this distance is no more than 30 kilometers.

[0045] In this embodiment of the application, the first empty run constraint and the second empty run constraint are considered simultaneously during the combination of transportation routes, which can not only improve the empty run situation, but also help to improve transportation efficiency.

[0046] In some embodiments of this application, the route combination constraint further includes at least one of: time connection constraint and attribute constraint; wherein, the time connection constraint is used to constrain the transportation time between different transportation routes in the same initial route set; the attribute constraint is used to constrain the attributes of the vehicles used by different transportation routes in the same initial route set.

[0047] It should be noted that time-connection constraints can prevent overlaps or conflicts in transport times between different transport routes within the same initial route set. Attribute constraints can utilize vehicle attributes to facilitate smoother cargo connections between different transport routes within the same initial route set. In some embodiments, vehicle attributes include tonnage, vehicle type, volume, destination, and cargo type. Therefore, route combination constraints may also include at least one constraint from Table 1 below. Here, the vehicle and package constitute the initial route set.

[0048] Table 1

[0049] In this embodiment, the addition of time coherence constraints and attribute constraints can further improve the quality of the combined results.

[0050] In some embodiments of this application, multiple transport routes are combined according to route combination constraints to obtain an initial route set, including:

[0051] Using the number of transport routes in the combination as the depth, a depth-first search algorithm is used to combine multiple transport routes into at least one initial route set; wherein, in the process of combining multiple transport routes, each transport route combined into the initial route set satisfies the route combination constraint.

[0052] It should be noted that the depth-first search algorithm can also be called the depth-first search algorithm (DFS), which will not be elaborated here. Understandably, in the process of continuously combining transportation routes using the depth-first search algorithm, the searched transportation routes must satisfy the route combination constraints to be successfully combined / inserted into the corresponding combinations.

[0053] For example, you can set the depth search function Search(S,H)now ,L jdg Flag, L a ), that is, [the input parameters are (root node, current depth, check set, Flag, and the set of bicycles in the root node)].

[0054] First, iterate through S and N. S Transportation route n in B: If B a Insert L jdg If the attribute constraints, time continuity constraints, and empty run constraints are satisfied, then [B] will be... a S, S front S Sfront ...(If Flag is not empty, proceed to Flag)] Insert L in order a If Flag = n, terminate all searches and return. If B a Insert L jdg The system satisfies attribute constraints and time continuity constraints, but not the empty run constraint. At this point, it checks if the depth constraint is satisfied; if Flag is empty and H... now +1≤H max Or, Flag is not empty and H now +1≤H F max Perform the next level search on n, n front =S, execute Search(n,H) now +1,L jdg +B n Flag, L a In other cases, skip n.

[0055] If N S If the result is empty, or if the search for the next level of S still fails to find a new Flag, then return to the previous level S. front Conduct in-depth searches for other subsequent transportation routes.

[0056] The explanations of the above parameters are as follows: B a This indicates the bound transport line (including a) of transport line a; if there is no bound line, it is simply a; L a This represents the single-vehicle execution sequence with transportation route 'a' as the root node, a set of transportation routes, and initial element B. a L jdg Represents the requirement check set, used for transportation route insertion checks; Flag represents the requirement flag that satisfies all constraints; H now H max , S and S' represent the current search depth, the maximum search depth before the Flag is found, and the maximum search depth after the Flag is found, respectively. front , representing the current search request and the previous search request of S, respectively; T maxThis indicates the number of times the search can be extended, meaning that after finding one Flag, at most a few new Flags can be found; N S This represents the set of lines in the pool to be combined that are in the state of 'uncombined', which is the search range of S.

[0057] Regarding the definition of the depth search function mentioned above, initialization can be performed first when generating the initial set of routes. Sort the pool of routes to be combined in ascending order according to the planned arrival time of the first task; set the status of each transport route r in the pool of routes to be combined to 'uncombined'. Then, for each transport route r in the pool of routes to be combined, perform the following operations sequentially: a) If the status of r is 'combined', skip it; otherwise, proceed to the following steps; b) L r ={r}, Flag=null, perform a depth search on the transportation route r, and execute the depth search function Search(r,0,L) r Flag, L r After the search is complete, proceed to step c; c) If Flag changes, start a new depth search from Flag, executing Search(Flag, 0, L). r Flag, L r If the Flag remains unchanged after execution, terminate and proceed to step d. Repeat step c for a maximum of T. max Next. d) The final L r As an initial set of lines, output: if Flag is not empty, then L r All transport routes are marked as 'combined'; all initial route sets are output as a combined initial solution.

[0058] In this embodiment of the application, an initial set of lines can be obtained quickly by means of a depth search algorithm.

[0059] In some embodiments of this application, obtaining multiple transportation routes in a logistics network includes: obtaining each transportation route in the logistics network; selecting transportation routes that meet target conditions from each transportation route in the logistics network; wherein the target conditions include: a single vehicle can perform all schedules of the transportation route; and selecting transportation routes that meet the target conditions as multiple transportation routes in the logistics network.

[0060] It should be noted that whether a single vehicle can complete all shifts on a transportation route can be determined based on the distance of the route. If the distance of the transportation route is too large, multiple vehicles are needed to complete the route, which would not meet the target conditions. Therefore, in the embodiments of this application, the distance of the transportation routes is usually not too large, thus the computational complexity is relatively low.

[0061] To effectively address different business scenarios, after acquiring multiple transportation routes within the logistics network, the method further includes:

[0062] Determine the scale of the transportation routes in the logistics network; if the scale of the transportation routes is greater than or equal to the target scale threshold, perform the step of combining multiple transportation routes according to the route combination constraint to obtain an initial route set; if the scale of the transportation routes is less than the target scale threshold, combine multiple transportation routes through an exhaustive algorithm to obtain an exhaustive route set; select the optimal exhaustive route set as the route combination result and output it.

[0063] It should be noted that the scale of the logistics network's transportation routes can be the number of transportation routes. In some embodiments, a quantity threshold can be preset. After determining the number of transportation routes in the logistics network, if the number is greater than or equal to the quantity threshold, the step of combining multiple transportation routes according to route combination constraints is executed to obtain an initial route set. Otherwise, an exhaustive algorithm is used to combine multiple transportation routes to obtain an exhaustive route set; the optimal exhaustive route set is selected as the route combination result and output. That is, based on different transportation route scales of the logistics network, different algorithms can be selected to generate route combination results. For business scenarios with a small transportation route scale, the exhaustive algorithm will not consume too much time, and all possible combinations will not be missed. The optimal solution selected from these combinations will certainly not enter a local optimum situation.

[0064] In some embodiments, during the process of generating route combination results using an exhaustive algorithm, the route combination cost can be set as the global objective, that is, the weighted cost of vehicle usage cost and route combination cost is minimized.

[0065] Formula 1:

[0066] Furthermore, in the final route combination result, each transport route can only appear in the route combination of one vehicle:

[0067] Formula 2:

[0068] In Formula 1 and Formula 2 above, x p = {0, 1}, where 1 indicates that bicycle p is selected as a bicycle package / initial route set, and 0 indicates that it is not selected, where p ∈ P. The output can be x. p The set of single vehicles with a value of 1 is used as the final route combination result. D represents the demand set / transportation route set, and d represents any transportation route in the demand set / transportation route set; P represents the set of single-vehicle route combinations entering the model, or simply the single-vehicle set, and p represents any single vehicle in the single-vehicle set; P d This represents the set of vehicles containing transportation route d in the execution sequence; c p Let α represent the transportation route combination cost of a single vehicle p; α represents the global vehicle cost weight; and β represents the global route combination cost weight.

[0069] In this embodiment, different business scenarios can be reasonably addressed, and the quality of line combination results can be improved as much as possible while ensuring response speed.

[0070] In some embodiments of this application, the line combination constraint further includes at least one of: inter-line constraint, packet relaxation constraint, and overall packet constraint;

[0071] Among them, the inter-line constraint is used to constrain whether two transport lines can be combined, the packet relaxation constraint is used to constrain the total transport time of all transport lines in the current combination, and the packet overall constraint is used to constrain the verification of all transport lines in the current combination.

[0072] It should be noted that, in order to speed up the combination process and increase the search scale during the combination process, the embodiments of this application distinguish between line constraints, package relaxation constraints and package overall constraints.

[0073] Inter-route constraints: These determine whether two transport routes can be combined, acting as a pruning mechanism to reduce many infeasible combinations. For example, inter-route constraints can include empty run distance constraints between two transport routes and waiting time constraints between two transport routes.

[0074] Packet relaxation constraint: This involves determining in advance whether a route combination could potentially become a packet. If so, the search can continue; otherwise, it terminates early. For example, a packet relaxation constraint could be the maximum duration of a vehicle / packet. That is, the overall duration of the vehicle / packet (from the arrival of the vehicle on the first transport route to the unloading on the last transport route) must be within a certain range.

[0075] Package overall constraints: Use all constraints to validate the combination. If it passes, output the combination; if any constraint fails the validation, the validation fails and ends early. For example, package overall constraints can be empty-running rate, vehicle-package efficiency, etc., as shown in Table 1 above.

[0076] In this embodiment of the application, the constraints of the full-package line combination are divided into inter-line constraints, packet relaxation constraints, and overall packet constraints, which can speed up the combination process and increase the search scale during the combination process.

[0077] In some embodiments of this application, obtaining multiple transport routes in a logistics network includes:

[0078] Obtain multiple transportation routes corresponding to a target area in the logistics network, where the target area is any area of ​​the logistics network.

[0079] It should be noted that when the logistics network is large in scale, the number of its transportation routes is usually enormous, and directly combining them would typically be a lengthy process. Furthermore, some business requirements may only require combining transportation routes for specific areas within the logistics network. Therefore, this embodiment can obtain only the transportation routes corresponding to a specific target area in the logistics network and then optimize their combination. This provides a finer granularity in the combination optimization process, meeting more refined business needs. In other embodiments, transportation routes for different areas of the logistics network can be divided into different route pools, and then combination optimization can be performed on the transportation routes in each route pool, i.e., the steps of combining transportation routes and outputting a set of routes described above. This way, the number of transportation routes in each route pool is not too large, allowing for rapid response.

[0080] In this embodiment, transportation routes in only certain areas of the logistics network can be combined. This allows for finer-grained optimization, meeting more specific business needs. Furthermore, different areas of the logistics network can be managed separately, improving the response speed of route combinations.

[0081] In some embodiments of this application, obtaining multiple transport routes in a logistics network includes:

[0082] Obtain information on each transportation route and its schedule in the logistics network; merge the schedules of each transportation route based on its schedule information to obtain multiple transportation routes.

[0083] It should be noted that there may be connections between transportation routes within a logistics network, and these connections can be used to reduce the number of routes. For example, one transportation route departs from location A to location B, with departures Monday through Wednesday. Another transportation route also departs from location A to location B, with departures Thursday through Friday. By merging the schedules of these two routes, a single transportation route will be generated, also departing from location A to location B, with departures Monday through Friday. Of course, the connections between transportation routes are not limited to the aforementioned departure schedules; for example, they could also include the monthly number of trips made by the transportation route.

[0084] In this embodiment of the application, by merging schedules, the number of transportation routes can be reduced, thereby improving the response speed of route combinations.

[0085] According to another aspect of this application, a method for combining transportation routes is provided, as shown in Figure 2. This method includes:

[0086] S201: Obtain multiple transportation routes in the logistics network.

[0087] S202: According to the route combination constraint, multiple transport routes are combined to obtain an initial route set; wherein, the route combination constraint includes: a first empty run constraint, which is used to constrain the empty run distance and / or empty run time between different routes in the same initial route set.

[0088] S203: Based on the initial set of routes, multiple transport routes are combined in multiple rounds according to the tabu search algorithm to obtain multiple rounds of combination results. Each round of combination results includes multiple intermediate route sets.

[0089] S204: Select the optimal combination result from each round of combination results as the line combination result and output it.

[0090] It should be noted that steps S201-S202 are the same as S101-S102 in the above embodiments of the invention, and will not be repeated here. Tabu search is a modern heuristic algorithm. Its basic idea is to avoid repeated searches by recording and selecting the optimization process already performed, using a flexible "memory" technique, thereby escaping local optima and achieving global optimization. The tabu search algorithm starts from an initial feasible solution, selects a series of specific search directions (movements) as trials, and chooses the movement that causes the most change in a specific objective function value. Then, the tabu table is updated, and the above process is repeated until the stopping rule is met. In this embodiment, during the multi-round combination process according to the tabu search algorithm, the initial set of routes is the initial feasible solution mentioned above. Multiple rounds of combination are considered as searching a series of specific search directions. Thus, there is a high probability that a global optimum will exist among the multiple combination results obtained. Finally, the optimal one is output as the combination result.

[0091] In some embodiments, the tabu search algorithm and the depth search algorithm have the same main process, the difference being that in the aforementioned depth search function Search(S,H) now ,L jdg Flag, L a During the process, the next level search set N of S is... S The prohibited transportation routes need to be removed. For example, a search dictionary named "Dict" can be set up. tabu In each 'key-value' pair, the key is a transportation route, and the value is a set of forbidden routes, indicating that when the current searched transportation route is the key, the next transportation route cannot be a route in the value set. The taboo update function is UpdateeTabu(L). r If L r Contains only B r No update is needed; terminate the function. Let L... r The length is l, and the i-th transport route is L.r [i]. For i = 1 to l - 1;

[0092] Take Dict tabu The key is L r The forbidden route set of [i], added to L r [i+1].

[0093] You can first add the search taboo dictionary Dict tabu Set to empty. Generate an initial solution according to the aforementioned depth-first search function, and during the generation of the initial solution, when searching node S, the next layer search set N... S Remove Dict tabu The pool contains transportation routes. After searching each transportation route r in the pool of routes to be combined, L is obtained. r Then execute the tabu update function UpdateTabu(L) r The meaning of each parameter can be found in the parameter meanings section of the aforementioned depth search algorithm, and will not be repeated here.

[0094] In this embodiment, automatic combination of transportation routes can be achieved, thereby avoiding local optima caused by manual route combination. Simultaneously, the route combination constraints include a first empty-run constraint, which constrains the empty-run distance and / or empty-run time between different routes within the same initial route set. By taking empty-running into account during the route combination process, the resulting initial route set exhibits good performance in the empty-running dimension, mitigating vehicle empty-running issues. Furthermore, the final route combination result is obtained by combining a tabu search algorithm, further improving the quality of the route combination result.

[0095] In some embodiments of this application, selecting the optimal combination result from each round of combination results as the line combination result and outputting it includes:

[0096] The results of each round of combinations are scored according to the business scoring strategy to obtain the optimization score of each round of combinations. The business scoring strategy includes at least one scoring indicator among the number of vehicles used, waiting time, and empty running status. The optimization score is positively correlated with the degree of optimization of the combination result. The combination result with the highest optimization score is taken as the route combination result and output.

[0097] It should be noted that each round of combination results can be considered as an initial solution, from which the optimal one needs to be selected. In this embodiment, a business scoring strategy can be pre-set to evaluate the degree of optimization of the combination results. The higher the optimization score obtained, the higher the degree of optimization, and vice versa.

[0098] As shown in Figure 3, when applying the transportation route combination method in an enterprise system, the user can trigger the system to execute operations, and the system will output the relevant results according to the transportation route combination method. Specifically, the process includes:

[0099] S301: Preprocessing. First, screen compliant transport routes and add them to the route pool for combination. A compliant transport route is one where a single vehicle can execute all its weekday schedules. Second, obtain the empty mileage distance and empty mileage schedule between every two points in the logistics network to avoid redundant calculation time caused by repeated requests and requests for duplicate transport routes during route combination. Third, analyze the constraints of different package types based on business requirements or actual manual combination. There are two main types of constraints: 1) Attribute constraints: Different requirements within the same package, such as tonnage, transport mode, vehicle type, required volume, contract period, and the region to which the route belongs, will have relevant business constraints. The first type of constraint can be seen as a constraint that determines whether transport routes can be combined in pairs. 2) Empty mileage constraints: After the package is formed, relevant business constraints are applied to the empty mileage distance of the included transport routes.

[0100] S302: Generate an initial solution based on a depth-first search algorithm, and generate multiple versions of the initial solution based on a tabu search algorithm. This process is the same as the process of obtaining the initial route set and multi-round combination results in the above embodiments.

[0101] S303: Score and evaluate the initial solution for each version. The scoring and evaluation rules can be the business scoring strategy described in the above embodiments.

[0102] S304: Output the optimal initial solution.

[0103] In this embodiment of the application, by using a service scoring strategy, the route combination result with the highest degree of optimization can be output.

[0104] In some embodiments of this application, the route combination constraint further includes a second empty-run constraint, which is used to constrain the ratio of the total empty-run distance to the total transport mileage between different transport routes in the same initial route set.

[0105] In some embodiments of this application, the route combination constraint further includes at least one of: time connection constraint and attribute constraint; wherein, the time connection constraint is used to constrain the transportation time between different transportation routes in the same initial route set; the attribute constraint is used to constrain the attributes of the vehicles used by different transportation routes in the same initial route set.

[0106] In some embodiments of this application, multiple transport routes are combined according to route combination constraints to obtain an initial route set, including: using the number of transport routes in the combination as the depth, multiple transport routes are combined into at least one initial route set through a depth search algorithm; wherein, in the process of combining multiple transport routes, each transport route combined into the initial route set satisfies the route combination constraints.

[0107] In some embodiments of this application, obtaining multiple transportation routes in a logistics network includes: obtaining each transportation route in the logistics network; selecting transportation routes that meet target conditions from each transportation route in the logistics network; wherein the target conditions include: a single vehicle can perform all schedules of the transportation route; and selecting transportation routes that meet the target conditions as multiple transportation routes in the logistics network.

[0108] It should be noted that the method for combining transportation routes provided in this embodiment belongs to the same application concept as the method for combining transportation routes provided in the above embodiments of this application specification. For technical details not described in detail in this embodiment, please refer to the specific processing content of the method for combining transportation routes provided in the above embodiments of the specification. Here, it will not be repeated.

[0109] According to another aspect of this application, a method for combining transportation routes is provided, as shown in Figure 4. This method for combining transportation routes includes:

[0110] S401: In response to the user's target input, obtain multiple transportation routes in the logistics network and determine the response time limit;

[0111] S402: When the response time limit is less than or equal to the duration threshold, multiple transportation routes are combined according to the route combination constraint to obtain an initial route set; wherein, the route combination constraint includes: a first empty run constraint, which is used to constrain the empty run distance and / or empty run time between different routes in the same initial route set; the initial route set is used as the route combination result and output.

[0112] S403: When the response time limit is greater than the duration threshold, combine multiple transportation routes according to the route combination constraint to obtain an initial route set; based on the initial route set, combine multiple transportation routes in multiple rounds according to the tabu search algorithm to obtain multiple intermediate route sets; select the optimal combination result from the multiple intermediate route sets as the route combination result and output it.

[0113] Each round of combination results includes multiple sets of intermediate routes.

[0114] It should be noted that the response time limit can be a certain duration entered by the user when making the target input, or it can be a duration automatically determined by the system based on the current business scenario.

[0115] Understandably, in some scenarios, there are requirements for system response time, such as 15 minutes, 30 minutes, or 60 minutes. When there are many transportation routes in a logistics network, large-scale variable enumeration is difficult. In this case, a depth-first search algorithm can be used to first generate an initial solution, and then multiple versions of the initial solution (variable generation, i.e., generating multiple rounds of combined results using a tabu search algorithm) can be allocated based on the remaining time, followed by model solving. If the response time cannot support the generation of multiple versions of the initial solution, the initial solution generated by the depth-first search algorithm can be returned. And typically, the generation of this initial solution is on the order of minutes. In some embodiments, the search depth can also be limited to limit the search time, allowing for flexible constraints at each stage to address the issue of given time limits.

[0116] It is worth noting that the processes S402 and S403 described above are the same as those in the above embodiments, and will not be repeated here.

[0117] It should be noted that the method for combining transportation routes provided in this embodiment belongs to the same application concept as the method for combining transportation routes provided in the above embodiments of this application specification. For technical details not described in detail in this embodiment, please refer to the specific processing content of the method for combining transportation routes provided in the above embodiments of the specification. Here, it will not be repeated.

[0118] Exemplary device

[0119] In this embodiment of the application, a transportation route combination device is also provided, as shown in FIG5. The transportation route combination device includes: an acquisition module 501, used to acquire multiple transportation routes in a logistics network; a first combination module 502, used to combine the multiple transportation routes according to route combination constraints to obtain an initial route set; wherein, the route combination constraints include: a first empty-run constraint, which is used to constrain the empty-run distance and / or empty-run time between different routes in the same initial route set; and a first output module 503, used to determine and output the route combination result based on the initial route set. For example, the first output module 503 can be used to output the initial route set as the route combination result.

[0120] In some embodiments of this application, the route combination constraint further includes a second empty-run constraint, which is used to constrain the ratio of the total empty-run distance to the total transport mileage between different transport routes in the same initial route set.

[0121] In some embodiments of this application, the route combination constraint further includes at least one of: time connection constraint and attribute constraint; wherein, the time connection constraint is used to constrain the transportation time between different transportation routes in the same initial route set; the attribute constraint is used to constrain the attributes of the vehicles used by different transportation routes in the same initial route set.

[0122] In some embodiments of this application, the first combination module 502 is specifically used to combine multiple transportation routes into at least one initial route set by using the number of transportation routes in the combination as the depth; wherein, in the process of combining multiple transportation routes, each transportation route combined into the initial route set satisfies the route combination constraint.

[0123] In some embodiments of this application, the acquisition module 501 is specifically used to acquire each transportation route in the logistics network; to filter transportation routes that meet target conditions from each transportation route in the logistics network; wherein, the target conditions include: a single vehicle can perform all the schedules of the transportation route; and to designate the transportation routes that meet the target conditions as multiple transportation routes in the logistics network.

[0124] In some embodiments of this application, the apparatus further includes: a route scale module, used to determine the scale of the transportation routes of the logistics network; when the scale of the transportation routes is greater than or equal to a target scale threshold, performing a step of combining multiple transportation routes according to route combination constraints to obtain an initial route set; when the scale of the transportation routes is less than the target scale threshold, combining multiple transportation routes through an exhaustive algorithm to obtain an exhaustive route set; and selecting the optimal exhaustive route set as the route combination result and outputting it.

[0125] In this embodiment of the application, a transportation route combination device is also provided, as shown in FIG6. The transportation route combination device includes: an acquisition module 501, used to acquire multiple transportation routes in a logistics network; a first combination module 502, used to combine multiple transportation routes according to route combination constraints to obtain an initial route set; wherein, the route combination constraints include: a first empty-run constraint, which is used to constrain the empty-run distance and / or empty-run time between different routes in the same initial route set; a second combination module 504, used to combine multiple transportation routes in multiple rounds according to a tabu search algorithm based on the initial route set to obtain multiple round combination results, wherein each round combination result includes multiple intermediate route sets; and a second output module 505, used to select the optimal combination result from each round combination result as the route combination result and output it.

[0126] In some embodiments of this application, the second output module 505 is specifically used to score the combination results of each round according to the business scoring strategy to obtain the optimization score of each round of combination results; wherein, the business scoring strategy includes at least one scoring indicator among the number of vehicles used, waiting time, and empty running status; the optimization score is positively correlated with the degree of optimization of the combination results; the combination result with the highest optimization score is taken as the route combination result and output.

[0127] In some embodiments of this application, the route combination constraint further includes a second empty-run constraint, which is used to constrain the ratio of the total empty-run distance to the total transport mileage between different transport routes in the same initial route set.

[0128] In some embodiments of this application, the route combination constraint further includes at least one of: time connection constraint and attribute constraint; wherein, the time connection constraint is used to constrain the transportation time between different transportation routes in the same initial route set; the attribute constraint is used to constrain the attributes of the vehicles used by different transportation routes in the same initial route set.

[0129] In some embodiments of this application, the first combination module 502 is specifically used to combine multiple transportation routes into at least one initial route set by using the number of transportation routes in the combination as the depth; wherein, in the process of combining multiple transportation routes, each transportation route combined into the initial route set satisfies the route combination constraint.

[0130] In some embodiments of this application, the acquisition module 501 is specifically used to acquire each transportation route in the logistics network; to filter transportation routes that meet target conditions from each transportation route in the logistics network; wherein, the target conditions include: a single vehicle can perform all the schedules of the transportation route; and to designate the transportation routes that meet the target conditions as multiple transportation routes in the logistics network.

[0131] In some embodiments of this application, the apparatus further includes: a route scale module, used to determine the scale of the transportation routes of the logistics network; when the scale of the transportation routes is greater than or equal to a target scale threshold, performing a step of combining multiple transportation routes according to route combination constraints to obtain an initial route set; when the scale of the transportation routes is less than the target scale threshold, combining multiple transportation routes through an exhaustive algorithm to obtain an exhaustive route set; and selecting the optimal exhaustive route set as the route combination result and outputting it.

[0132] In this embodiment of the application, a transportation route combination device is also provided, as shown in FIG7. The transportation route combination device includes: a response module 701, used to respond to the user's target input, acquire multiple transportation routes in the logistics network, and determine the response time limit; a first processing module 702, used to combine multiple transportation routes according to route combination constraints to obtain an initial route set when the response time limit is less than or equal to a time threshold; wherein the route combination constraints include: a first empty run constraint, which is used to constrain the empty run distance and / or empty run time between different routes in the same initial route set; and output the initial route set as the route combination result; a second processing module 703, used to combine multiple transportation routes according to route combination constraints to obtain an initial route set when the response time limit is greater than the time threshold; based on the initial route set, use a tabu search algorithm to perform multiple rounds of combination on multiple transportation routes to obtain multiple rounds of combination results, wherein each round of combination results includes multiple intermediate route sets; and select the optimal combination result from each round of combination results as the route combination result and output it.

[0133] It should be noted that the transportation line combination device provided in this embodiment belongs to the same application concept as the transportation line combination method provided in the above embodiments of this application specification. It can execute the transportation line combination method provided in any of the above embodiments of this specification, and specifically execute the corresponding functional modules and beneficial effects of the transportation line combination device. For technical details not described in detail in this embodiment, please refer to the specific processing content of the transportation line combination method provided in the above embodiments of the specification. Here, it will not be repeated.

[0134] Exemplary electronic devices

[0135] Another embodiment of this application also proposes an electronic device. Please refer to FIG8, which is a schematic diagram of the structure of the electronic device provided in the embodiment of this application. An exemplary embodiment of this specification also provides an electronic device, including: a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the steps in the method for combining transportation lines according to various embodiments of this specification as described in the above embodiments.

[0136] The internal structure of the electronic device is shown in Figure 8. The electronic device includes a processor, memory, network interface, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it follows the steps of the method for combining transport lines according to various embodiments of this specification as described in the above embodiments.

[0137] The processor may include the main processor, as well as baseband chips, modems, etc.

[0138] The memory stores a computer program that executes the technical solution of this invention, and may also store an operating system and other key business functions. Specifically, the computer program may include program code, which includes computer operation instructions. More specifically, the memory may include read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), other types of dynamic storage devices capable of storing information and instructions, disk storage, flash memory, etc.

[0139] The processor can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present invention. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0140] Input devices may include devices that receive data and information input by the user, such as keyboards, mice, cameras, scanners, light pens, voice input devices, touch screens, pedometers, or gravity sensors.

[0141] Output devices may include devices that allow information to be output to the user, such as displays, printers, speakers, etc.

[0142] The communication interface may include any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0143] The processor executes the computer program stored in the memory and calls other devices, which can be used to implement the various steps of any of the transportation route combination methods provided in the above embodiments of this application.

[0144] The electronic device may also include a display component and a voice component. The display component may be a liquid crystal display screen or an e-ink display screen. The input device of the electronic device may be a touch layer covering the display component, or a button, trackball or touchpad set on the casing of the electronic device, or an external keyboard, touchpad or mouse, etc.

[0145] Those skilled in the art will understand that the structure shown in Figure 8 is merely a block diagram of a portion of the structure related to the solution in this specification, and does not constitute a limitation on the electronic device to which the solution in this specification is applied. A specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0146] In addition to the methods and devices described above, the method for combining transport routes provided in the embodiments of this specification can also be a computer program product, which includes a computer program that, when run by a processor, causes the processor to perform the steps in the method for combining transport routes according to various embodiments of this specification as described in the "Exemplary Methods" section above.

[0147] The computer program product described herein can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments described herein. These programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0148] Furthermore, embodiments of this specification also provide a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor of the steps in the method of combining transport routes according to various embodiments of this specification as described in the "Exemplary Methods" section above.

[0149] It is understood that the specific examples in this document are only intended to help those skilled in the art better understand the implementation methods of this specification, and are not intended to limit the scope of this specification.

[0150] It is understood that in the various embodiments described in this specification, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments described in this specification.

[0151] It is understood that the various implementation methods described in this specification can be implemented individually or in combination, and the implementation methods in this specification are not limited in this respect.

[0152] Unless otherwise stated, all technical and scientific terms used in the embodiments of this specification have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of this specification. The term "and / or" as used in this specification includes any and all combinations of one or more of the associated listed items. The singular forms "a," "the," and "the" as used in the embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0153] It is understood that the processor in the embodiments of this specification can be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method embodiments can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this specification. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this specification can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0154] It is understood that the memory in the embodiments of this specification may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may be random access memory (RAM). It should be noted that the memory in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0155] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this specification.

[0156] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the aforementioned method implementations, and will not be repeated here.

[0157] In the several embodiments provided in this specification, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0158] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0159] In addition, the functional units in the various embodiments of this specification can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0160] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of this specification, in essence, or the parts that contribute to the prior art, or parts of the technical solutions, can be embodied in the form of software products. These computer software products are stored in a storage medium and include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this specification. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0161] The above description is merely a specific embodiment of this specification, but the scope of protection of this specification is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this specification should be included within the scope of protection of this specification. Therefore, the scope of protection of this specification should be determined by the scope of the claims.

Claims

1. A method for combining transportation routes, characterized in that, The method includes: Obtain multiple transportation routes within the logistics network; According to the route combination constraint, the multiple transportation routes are combined to obtain an initial route set; wherein, the route combination constraint includes: a first empty run constraint, which is used to constrain the empty run distance and / or empty run time between different routes in the same initial route set; The route combination result is determined and output based on the initial route set.

2. The method according to claim 1, characterized in that, The route combination constraint also includes a second empty-run constraint, which is used to constrain the ratio of the total empty-run distance to the total transport mileage among different transport routes in the same initial route set.

3. The method according to claim 1 or 2, characterized in that, The route combination constraints also include at least one of the following: time connection constraints and attribute constraints; The time connection constraint is used to constrain the transportation time between different transportation routes in the same initial route set; the attribute constraint is used to constrain the attributes of the vehicles used by different transportation routes in the same initial route set.

4. The method according to any one of claims 1 to 3, characterized in that, The process of combining the multiple transportation routes according to route combination constraints to obtain an initial route set includes: Using the number of transport routes in the combination as the depth, a depth-first search algorithm is used to combine the multiple transport routes into at least one initial route set; wherein, during the combination of the multiple transport routes, each transport route combined into the initial route set satisfies the route combination constraint.

5. The method according to any one of claims 1 to 4, characterized in that, The acquisition of multiple transportation routes in the logistics network includes: Obtain each transport route in the logistics network; Select transport routes that meet the target conditions from each transport route in the logistics network; wherein, the target conditions include: a single vehicle can perform all schedules of the transport route; The transportation routes that meet the target conditions are designated as the multiple transportation routes in the logistics network.

6. The method according to any one of claims 1 to 5, characterized in that, After obtaining multiple transportation routes in the logistics network, the method further includes: Determine the scale of the transportation routes of the logistics network; If the size of the transportation route is greater than or equal to the target size threshold, the step of combining the multiple transportation routes according to the route combination constraint to obtain an initial route set is performed. If the size of the transportation route is less than the target size threshold, the multiple transportation routes are combined using an exhaustive algorithm to obtain an exhaustive route set; the optimal exhaustive route set is selected as the route combination result and output.

7. The method according to any one of claims 1 to 6, characterized in that, The step of determining and outputting the route combination result based on the initial route set includes: The initial set of routes is used as the route combination result and output.

8. The method according to any one of claims 1 to 6, characterized in that, The step of determining and outputting the route combination result based on the initial route set includes: Based on the initial set of routes, the multiple transportation routes are combined in multiple rounds according to the tabu search algorithm to obtain multiple rounds of combination results. Each round of combination results includes multiple intermediate route sets. The optimal combination result is selected from the results of each round of combinations and output as the line combination result.

9. The method according to claim 8, characterized in that, The step of selecting the optimal combination result from the results of each round of combinations as the route combination result and outputting it includes: The results of each round of combinations are scored according to a business scoring strategy to obtain an optimization score for each round of combinations; wherein, the business scoring strategy includes at least one scoring indicator among the number of vehicles used, waiting time, and empty running status; the optimization score is positively correlated with the degree of optimization of the combination results; The combination with the highest optimization score is taken as the line combination result and output.

10. The method according to any one of claims 1 to 6, characterized in that, The acquisition of multiple transportation routes in the logistics network includes: In response to the user's target input, the system retrieves the multiple transportation routes in the logistics network and determines the response time limit. Wherein, when the response time limit is less than or equal to the duration threshold, the step of determining and outputting the line combination result based on the initial line set includes: using the initial line set as the line combination result and outputting it. If the response time limit is greater than the duration threshold, the step of determining and outputting the route combination result based on the initial route set includes: using the initial route set as a basis, performing multiple rounds of combination on the multiple transportation routes according to the tabu search algorithm to obtain multiple rounds of combination results, wherein each round of combination results includes multiple intermediate route sets; selecting the optimal combination result from each round of combination results as the route combination result and outputting it.

11. A combination device for a transportation line, characterized in that, include: The acquisition module is used to acquire multiple transportation routes in the logistics network; The first combination module is used to combine the multiple transportation routes according to the route combination constraints to obtain an initial route set; wherein, the route combination constraints include: a first empty run constraint, which is used to constrain the empty run distance and / or empty run time between different routes in the same initial route set; The first output module is used to determine and output the line combination result based on the initial line set.

12. The apparatus according to claim 11, characterized in that, The route combination constraint also includes a second empty-run constraint, which is used to constrain the ratio of the total empty-run distance to the total transport mileage among different transport routes in the same initial route set.

13. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements a method for combining transport routes as described in any one of claims 1 to 10.

14. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method for combining transport routes as described in any one of claims 1 to 10.

15. A computer program product, characterized in that, include: A computer program, when executed by a processor, implements the method of combining transport routes as described in any one of claims 1 to 10.

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